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Data Scientist (development)
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Talent Review Date: 07/18/2025
Recent position
Business Intelligence
Intelligence Developer
09/01/2024 - 05/14/2025Job Description
• Designed and maintained Power BI dashboards to track KPIs across organ donation and finance, improving executive visibility and operational decisions. • Built and optimized complex SQL queries to extract, clean, and transform CRM data, increasing reporting accuracy by 30%. • Collaborated with business, technical, and clinical teams to define KPIs, automate reports (SSRS to Power BI), and improve stakeholder engagement. • Used Power Query, DAX, and Excel to shape data for self-serve analytics and scalable reporting. • Led a migration to Power BI Service, enhancing scalability, version control, and real-time data delivery. • Contributed to insight-driven strategies for retention and process optimization through BI tools and data storytelling.
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Top candidates, pre-vetted — no hire, no charge
Talent Review Date: 07/18/2025
Video presentation
WORKPLACES
Job description
• Designed and maintained Power BI dashboards to track KPIs across organ donation and finance, improving executive visibility and operational decisions. • Built and optimized complex SQL queries to extract, clean, and transform CRM data, increasing reporting accuracy by 30%. • Collaborated with business, technical, and clinical teams to define KPIs, automate reports (SSRS to Power BI), and improve stakeholder engagement. • Used Power Query, DAX, and Excel to shape data for self-serve analytics and scalable reporting. • Led a migration to Power BI Service, enhancing scalability, version control, and real-time data delivery. • Contributed to insight-driven strategies for retention and process optimization through BI tools and data storytelling.
Job description
• Designed D3.js and Python-based data visualizations for bi-annual cellular dataset releases, improving visual clarity and usability for research partners • Preprocessed large biological datasets using Excel and Python for integration into visualization pipelines, accelerating insight generation. • Maintained a Git-based CI/CD workflow to ensure collaboration, reduce errors, and streamline visualization deployment. • Collaborated with a cross-functional research team to translate biological data into interpretable insights for scientific publications. • Contributed to scalable, reusable visualization templates aligned with data storytelling and reproducibility best practices
Job description
• Led instruction for 100+ students on Python, Power BI, and data storytelling, improving data visualization skills by 20%. • Designed hands-on modules using real-world datasets to teach dashboarding, network analysis (Gephi), and exploratory analytics. • Mentored students in interpreting complex data using SQL, R, and statistical methods, reinforcing analytical thinking. • Communicated technical concepts to diverse learners, strengthening clarity and cross-functional communication skills.
Job description
• Developed Python scripts for ETL automation and Oracle/Redshift optimization, improving data quality by 20% and retrieval speed by 30%. • Created and maintained Tableau and QuickSight dashboards to visualize performance metrics and support executive reporting. • Managed structured datasets using AWS S3, enabling secure storage and access for daily analytics workflows. • Streamlined ETL workflows and scalable data models using SQL, R, and Unix, while automating reporting via Control-M for cross-functional analytics delivery. • Conducted A/B testing and applied statistical methods (chi-square, t-tests) to evaluate business strategies and inform product decisions..
Recent position
09/01/2024
-
05/14/2025
Skills
Neo4j
JIRA
Management
MongoDB
Data Science
Data Analysis
MATLAB
Data Storage
Data Modeling
Innovation
Github
Google Analytics
Salesforce
MySQL
Expense Analysis
Financial Analysis
IBM DB2
Analytics
Process Optimization
Data Storytelling
Python (Programming Language)
Microsoft Excel
Business Strategies
Customer Relationship Management
Amazon Web Services
Usability
Communication
Unix
Visualization
SQL (Programming Language)
R (Programming Language)
Dashboard
Reproducibility
Tableau (Business Intelligence Software)
Amazon S3
Gephi
Finance
Git (Version Control System)
Statistical Methods
C (Programming Language)
Version Control
Collaboration
Control-M (Batch Scheduling Software)
Power BI
Dataset
Automation
Research
Microsoft Visual Studio
Statistical Analysis
Databricks
Expense Management
PostgreSQL
Business Intelligence
NoSQL
Statistical Modeling
Extract Transform Load (ETL)
D3.js (Javascript Library)
Network Analysis
Storytelling
Data Quality
Diverse Learners
Scalability
Templates
Data Visualization
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Talent Review Date: 07/20/2025
Recent position
Data Science Student
Data Science Student Teacher
05/01/2024 - 01/01/2025Job Description
• Led machine learning and statistical analysis labs, ensuring students mastered theoretical concepts and real-world applications. • Designed interactive labs on model evaluation, feature selection, and bias-variance tradeoff, fostering analytical problem-solving. • Created teaching materials on neural networks, computer vision, and statistical analysis, ensuring clarity and practical application.
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Talent Review Date: 07/20/2025
Video presentation
WORKPLACES
Job description
• Led machine learning and statistical analysis labs, ensuring students mastered theoretical concepts and real-world applications. • Designed interactive labs on model evaluation, feature selection, and bias-variance tradeoff, fostering analytical problem-solving. • Created teaching materials on neural networks, computer vision, and statistical analysis, ensuring clarity and practical application.
Job description
• Designed and evaluated classification models using cross-validation, ROC-AUC, and SHAP to guide marketing campaign targeting. • Applied Natural Language Processing (NLP) using spaCy and BERT to extract trends from customer feedback and online reviews. • Conducted A/B testing, measured KPIs, and analyzed experiment lift using Python to support iterative product improvements. • Performed churn analysis using logistic regression to identify at-risk customers, driving retention strategies that reduced attrition. • Identified inefficiencies in workflows using process mining and business rules modeling, delivering actionable recommendations. • Developed requirement documents and functional specs by translating market trends and performance analysis into business needs. • Analyzed CRM data to uncover underperforming segments and recommended territory realignment strategies that improved sales. • Measured ROI across digital channels using UTM tagging and conversion tracking, optimizing campaign spend allocation. • Created audience segmentation models using clustering algorithms to enhance personalization in marketing automation platforms. • Built Tableau dashboards to track product KPIs (activation, engagement, retention), enabling real-time visibility for product teams. • Worked with stakeholders across operations and finance to define KPIs and analyze cost-saving opportunities using SQL models.
Recent position
05/01/2024
-
01/01/2025
Skills
Analytics
Scikit-Learn (Python Package)
Microsoft Excel
Time Series
Amazon Web Services
Jupyter
Pattern Recognition
Visualization
Data Science
Personalized Service
Data Analysis
Marketing Automation
Xgboost
Github
Power BI
Streamlining
Pandas (Python Package)
Sales Analysis
Research
Python (Programming Language)
Automation
Computer Vision
Operations
Customer Relationship Management
SQL (Programming Language)
Bit Error Rate Tester (BERT)
Conversion Tracking
Process Mining
Algorithms
Dashboard
Marketing
Tableau (Business Intelligence Software)
Git (Version Control System)
Machine Learning
Finance
Sales
Feature Selection
Performance Analysis
Logistic Regression
Teaching
SpaCy (NLP Software)
Cloud Computing
Predictive Modeling
Seaborn
Plotly
Bitcoin
Data Retrieval
Scripting
Feature Engineering
Customer Engagement
Jupyter Notebook
Data Visualization
VS Code
Matplotlib (Python Package)
Statistical Modeling
Statistical Analysis
Audience Segmentation
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Top candidates, pre-vetted — no hire, no charge
Talent Review Date: 07/08/2025
Recent position
Data Scientist | Data Analyst | Programmer
Data Scientist
02/01/2022 - 05/05/2025Job Description
At Chubb Insurance Company, as a Data Scientist, I significantly improved a Modified GLM model’s F1-score by 22% through Programmatic Labeling, enhancing classification accuracy and reducing manual annotation efforts. I collaborated with Underwriters to design A/B tests for evaluating the impact of machine learning-driven quote prioritization strategies. Additionally, I implemented a Graph-based Community Detection solution, leading to a ~24% increase in business volume by providing instant quotes to small businesses. I took ownership of the end-to-end machine learning pipeline for predicting propensity to bind, resulting in a positive income impact of $4 million. My work involved developing models using XGBoost, GLM, and Decision Trees for tabular data, and BERT for unstructured data like webtext on Azure ML. I also created visualizations using Matplotlib and Plotly to present complex data insights to non-technical stakeholders, ensuring clear communication of the project's benefits.
Smarter hiring with AI
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Talent Review Date: 07/08/2025
Video presentation
WORKPLACES
Job description
At Chubb Insurance Company, as a Data Scientist, I significantly improved a Modified GLM model’s F1-score by 22% through Programmatic Labeling, enhancing classification accuracy and reducing manual annotation efforts. I collaborated with Underwriters to design A/B tests for evaluating the impact of machine learning-driven quote prioritization strategies. Additionally, I implemented a Graph-based Community Detection solution, leading to a ~24% increase in business volume by providing instant quotes to small businesses. I took ownership of the end-to-end machine learning pipeline for predicting propensity to bind, resulting in a positive income impact of $4 million. My work involved developing models using XGBoost, GLM, and Decision Trees for tabular data, and BERT for unstructured data like webtext on Azure ML. I also created visualizations using Matplotlib and Plotly to present complex data insights to non-technical stakeholders, ensuring clear communication of the project's benefits.
Job description
At Avanade, I designed and developed dynamic Power BI dashboards for a major retail client, utilizing data from Dynamics CRM to provide actionable insights. I also played a key role in developing ETL pipelines, transforming and moving data from various legacy systems to Azure DataLake for a leading insurance firm, streamlining data processes and enabling more efficient data access and analysis.
Job description
At Cognizant Technology Solutions, I developed a chatbot using AWS Lex and AWS Lambda to automate the search for over 50,000 parts for a major manufacturing firm. I also automated the ticket creation process using NLP and the MS Azure Bot Framework, reducing customer service time by 30%. I wrote SQL queries for data extraction from MS Azure Cosmos DB to optimize an autocomplete service, improving latency by 40%. Additionally, I used Pandas to transform raw data and developed an Ibex dashboard for sentiment analysis, improving virtual agent performance and increasing customer satisfaction by 50%. My efforts also included semi-automating chatbot training, reducing training time by 40%. I was awarded the Mountain Mover award for outstanding performance in the second quarter of 2019.
Recent position
02/01/2022
-
05/05/2025
Skills
Sentiment Analysis
Surveys
SPARQL Protocol And RDF Query Language (SPARQL)
Tree Maps
Power BI
SQL (Programming Language)
NumPy (Python Package)
Emerging Technologies
Pandas (Python Package)
Jupyter
Communication
Social Media Campaigns
Github
LangChain
BIND (DNS Software)
Xgboost
Python (Programming Language)
Docker (Software)
Heroku
JavaScript (Programming Language)
Management
Research
Data Science
Anomaly Detection
Scikit-Learn (Python Package)
Dataset
Deep Learning
Social Media
Communications Management
Analytics
Customer Service
Node.js (Javascript Library)
Amazon Web Services
R (Programming Language)
AWS Lambda
Machine Learning
Complexity Reduction
Dashboard
Bit Error Rate Tester (BERT)
Chatbot
Bot Framework
Matplotlib (Python Package)
Multiple Models
Microsoft Power Platform
Lex (Software)
Data Engineering
Jupyter Notebook
Boosting
Prioritization
Unstructured Data
Tabular Data
Research Papers
PyTorch (Machine Learning Library)
Microsoft Azure
PySpark
Statistics
TensorFlow
Underwriting
Data Mining
Good Manufacturing Practices
Raw Data
Plotly
Extract Transform Load (ETL)
Azure Cosmos DB
Technology Solutions
python
SQL
R
Tableau
GitHub
Machine Learning
Supervised Learning
Unsupervised Learning
Docker
NodeJS
SPARQL
Deep Learning
GraphML
Your hiring pipeline, powered by AXIOM PRO.
Top candidates, pre-vetted — no hire, no charge
Talent Review Date: 07/16/2025
Recent position
data scientist
Data Scientist
01/01/2024 - 05/02/2025Job Description
• Designed and deployed scalable ETL pipelines using Python, SQL, Apache Airflow, and AWS Glue to automate ingestion, transformation, and loading of high-volume customer and transaction data into Snowflake and Redshift, improving data accessibility across departments. • Engineered real-time data streaming workflows using Apache Kafka and AWS Kinesis to support fraud detection, Smart Search recommendations, and credit risk analytics, enabling sub-second decision-making. • Developed modular, production-grade ELT workflows with dbt (data build tool) on Snowflake, improving data modeling efficiency and reducing transformation latency by 35% for financial dashboards. • Built and maintained centralized data lakes on AWS S3, establishing a robust data foundation for cross-functional ML, BI, and reporting use cases while optimizing storage costs using lifecycle policies. • Led integration of GenAI-powered Smart Search on Synchrony Marketplace using OpenAI's GPT models and FAISS vector stores, enabling personalized product recommendations and enhancing customer engagement. • Operationalized LLM-based analytics pipelines using Hugging Face Transformers and LangChain for entity extraction, document summarization, and semantic search, accelerating insights from unstructured data by 60%. • Developed and deployed ML pipelines on AWS SageMaker for credit scoring, churn prediction, and sentiment classification models, integrating with downstream workflows via Lambda and API Gateway. • Implemented data quality frameworks using Great Expectations and custom validation layers within Airflow DAGs, ensuring high data trust and compliance with regulatory reporting standards. • Optimized complex analytical queries on Snowflake and Redshift using clustering keys, partition pruning, and query profiling techniques, reducing report generation time by 50%. • Designed and version-controlled infrastructure with Terraform and AWS CloudFormation, automating provisioning of scalable, fault-tolerant components like Lambda, Glue Jobs, IAM, and S3 buckets. • Led schema design and dimensional modeling using Star and Snowflake schemas for customer analytics and financial data marts, boosting reporting performance and simplifying end-user consumption. • Built and maintained self-service data marts and APIs for Power BI, Tableau, and internal microservices, empowering business teams to access curated data with minimal engineering dependencies. • Collaborated with cross-functional teams (AI/ML, risk, customer experience) to deploy NLP solutions using spaCy, BERT, and TensorFlow for feedback classification, sentiment scoring, and call center automation. • Instrumented CI/CD pipelines for data and ML deployments using GitHub Actions and SageMaker Model Registry, reducing release cycles and ensuring model reproducibility in production. • Supported Synchrony's AI governance framework, ensuring responsible use of GenAI and ML tools through metadata tracking, model monitoring, and alignment with internal compliance protocols.
Smarter hiring with AI
Your hiring pipeline, powered by AXIOM PRO .
Top candidates, pre-vetted — no hire, no charge
Talent Review Date: 07/16/2025
Video presentation
WORKPLACES
Job description
• Designed and deployed scalable ETL pipelines using Python, SQL, Apache Airflow, and AWS Glue to automate ingestion, transformation, and loading of high-volume customer and transaction data into Snowflake and Redshift, improving data accessibility across departments. • Engineered real-time data streaming workflows using Apache Kafka and AWS Kinesis to support fraud detection, Smart Search recommendations, and credit risk analytics, enabling sub-second decision-making. • Developed modular, production-grade ELT workflows with dbt (data build tool) on Snowflake, improving data modeling efficiency and reducing transformation latency by 35% for financial dashboards. • Built and maintained centralized data lakes on AWS S3, establishing a robust data foundation for cross-functional ML, BI, and reporting use cases while optimizing storage costs using lifecycle policies. • Led integration of GenAI-powered Smart Search on Synchrony Marketplace using OpenAI's GPT models and FAISS vector stores, enabling personalized product recommendations and enhancing customer engagement. • Operationalized LLM-based analytics pipelines using Hugging Face Transformers and LangChain for entity extraction, document summarization, and semantic search, accelerating insights from unstructured data by 60%. • Developed and deployed ML pipelines on AWS SageMaker for credit scoring, churn prediction, and sentiment classification models, integrating with downstream workflows via Lambda and API Gateway. • Implemented data quality frameworks using Great Expectations and custom validation layers within Airflow DAGs, ensuring high data trust and compliance with regulatory reporting standards. • Optimized complex analytical queries on Snowflake and Redshift using clustering keys, partition pruning, and query profiling techniques, reducing report generation time by 50%. • Designed and version-controlled infrastructure with Terraform and AWS CloudFormation, automating provisioning of scalable, fault-tolerant components like Lambda, Glue Jobs, IAM, and S3 buckets. • Led schema design and dimensional modeling using Star and Snowflake schemas for customer analytics and financial data marts, boosting reporting performance and simplifying end-user consumption. • Built and maintained self-service data marts and APIs for Power BI, Tableau, and internal microservices, empowering business teams to access curated data with minimal engineering dependencies. • Collaborated with cross-functional teams (AI/ML, risk, customer experience) to deploy NLP solutions using spaCy, BERT, and TensorFlow for feedback classification, sentiment scoring, and call center automation. • Instrumented CI/CD pipelines for data and ML deployments using GitHub Actions and SageMaker Model Registry, reducing release cycles and ensuring model reproducibility in production. • Supported Synchrony's AI governance framework, ensuring responsible use of GenAI and ML tools through metadata tracking, model monitoring, and alignment with internal compliance protocols.
Job description
• Developed robust ETL pipelines using PySpark and Azure Data Factory to ingest and transform high-volume transactional data into Azure SQL Data Warehouse, reducing batch processing times by 40%. • Engineered real-time monitoring systems using Isolation Forests and Autoencoders to detect anomalies in supplier lead times and logistics delays, achieving 92% accuracy and reducing vendor penalties by 15%. • Built scalable data pipelines on Azure Databricks for structured and unstructured data, enabling seamless downstream ML model training and analytics consumption. • Implemented NLP-based sentiment analysis models using BERT and spaCy to analyze financial news and customer reviews, improving investment insights and decision-making frameworks. • Designed and deployed cloud-native data workflows on Azure, leveraging Data Lake Gen2, Azure Functions, and Event Hub for end-to-end data orchestration and stream processing. • Developed dynamic dashboards in Power BI and Tableau, visualizing supplier risk metrics and operational KPIs, resulting in a 25% improvement in procurement decisions. • Led development of Monte Carlo simulation models to assess supply chain risk and optimize sourcing strategies under demand variability, reducing inventory holding costs by 20%. • Automated A/B testing frameworks using statistical methods and Python libraries (Statsmodels, Scipy), enabling rapid experimentation for product and pricing strategies. • Collaborated with ML engineers to deploy forecasting models using XGBoost and Random Forest for demand prediction, increasing forecast accuracy by 20% and streamlining logistics. • Optimized big data pipelines with Spark and Delta Lake for scalable machine learning workloads, reducing compute costs and improving time to-insight for executive stakeholders. • Built speech-to-text and text-to-speech models using Azure Cognitive Services to automate customer service voice interactions, improving accessibility and reducing call center load. • Designed and implemented reusable data validation checks using Pytest and Great Expectations, enhancing trust in data and reducing manual QA efforts by 30%. • Streamlined DevOps for data workflows using Azure DevOps, Git, and automated CI/CD pipelines for faster deployment of analytics and data engineering releases. • Created reusable templates and modules for Databricks notebooks, enabling faster onboarding and consistent code practices across engineering teams. • Led cross-functional efforts to scale GenAI prototypes into production, supporting large-scale testing of NLP pipelines in a secure and distributed Azure environment.
Recent position
01/01/2024
-
05/02/2025
Skills
Jupyter
SAS (Software)
BigQuery
Analysis Of Variance (ANOVA)
SPSS (Statistical Software)
Agile Software Development
Scrum (Software Development)
Linux
Visualization
Pattern Recognition
JMP (Statistical Software)
Data Wrangling
Apache Spark
MySQL
Bash (Scripting Language)
Management
Network Bridging
Docker (Software)
Microsoft Excel
Continuous Integration
Time Series
Pandas (Python Package)
JIRA
Computer Vision
Storage Area Network (SAN)
Anomaly Detection
MongoDB
Scikit-Learn (Python Package)
Perl (Programming Language)
MATLAB
Data Analysis
SAP CRM
Microsoft Windows
Keras (Neural Network Library)
Digital Transformation
Data Science
NumPy (Python Package)
Critical Thinking
Communication
Azure Databricks
Reproducibility
R (Programming Language)
SpaCy (NLP Software)
Github
Amazon S3
Bit Error Rate Tester (BERT)
Batch Processing
Statsmodels
Machine Learning
LangChain
Customer Service
Xgboost
Data Streaming
Power BI
Statistical Methods
Governance
Apache Airflow
Forecasting
Git (Version Control System)
Airflow
Data Validation
Pruning
Sentiment Analysis
Procurement
Tableau (Business Intelligence Software)
Big Data
Streamlining
Application Programming Interface (API)
Data Modeling
Supply Chain
Fraud Detection
Azure Data Factory
Python (Programming Language)
Credit Risk
DevOps
Amazon Web Services
Transaction Data
SQL (Programming Language)
Text-To-Speech
Transformers (Electrical)
Apache Kafka
Experimentation
Azure DevOps
C (Programming Language)
Dimensional Modeling
Analytics
Scale (Map)
AWS Glue
Microservices
AWS SageMaker
Automation
Profiling (Computer Programming)
Data Visualization
Predictive Analytics
Long Short-Term Memory (LSTM)
Computer Science
PyCharm
Regression Analysis
PyTorch (Machine Learning Library)
Decision Making
Matplotlib (Python Package)
Statistics
Electronic Design Automation (EDA) Software
VS Code
Seaborn
Mathematics
Data Processing
MLflow
Statistical Analysis
Data Engineering
Data Mining
Query Optimization
Data Integrity
Ggplot2
Good Clinical Practices (GCP)
Product Management
Extract Transform Load (ETL)
Data Build Tool
Hugging Face Transformers
API Gateway
Databricks
SciPy
Azure Cognitive Services
Metadata
Data Quality
Unstructured Data
Data Pipelines
Customer Analytics
Risk Analytics
AWS Kinesis
Logistics
Scala (Programming Language)
Boosting
Azure Functions
Employee Onboarding
TensorFlow
Semantic Search
Autoencoders
PySpark
Financial Data
Transformation (Genetics)
Terraform
AWS CloudFormation
Data Lakes
Templates
Your hiring pipeline, powered by AXIOM PRO.
Top candidates, pre-vetted — no hire, no charge
Talent Review Date: 07/08/2025
Recent position
data scientist
Data Scientist
01/01/2025 - 05/02/2025Job Description
• Designed and fine-tuned a customer lifetime value (CLV) model using LightGBM, boosting marketing ROI by 18% quarter-over quarter. • Led migration of predictive analytics workflows to Azure Databricks, improving model training speeds by 45% and enabling large-scale data processing (~10M+ rows). • Built ML APIs using FastAPI and Docker, facilitating real-time integration of risk scoring models into customer service portals. • Conducted model monitoring via MLflow, setting drift thresholds and retraining alerts that decreased model performance decay by 30%. • Collaborated with cross-functional teams (engineering, product, marketing) to deliver scalable ML pipelines end-to-end.
Smarter hiring with AI
Your hiring pipeline, powered by AXIOM PRO .
Top candidates, pre-vetted — no hire, no charge
Talent Review Date: 07/08/2025
Video presentation
WORKPLACES
Job description
• Designed and fine-tuned a customer lifetime value (CLV) model using LightGBM, boosting marketing ROI by 18% quarter-over quarter. • Led migration of predictive analytics workflows to Azure Databricks, improving model training speeds by 45% and enabling large-scale data processing (~10M+ rows). • Built ML APIs using FastAPI and Docker, facilitating real-time integration of risk scoring models into customer service portals. • Conducted model monitoring via MLflow, setting drift thresholds and retraining alerts that decreased model performance decay by 30%. • Collaborated with cross-functional teams (engineering, product, marketing) to deliver scalable ML pipelines end-to-end.
Job description
• Developed a churn prediction system using XGBoost and PySpark, improving early detection of high-risk clients with 22% higher recall than previous heuristic methods. • Automated EDA workflows and feature generation for 12+ business use cases, cutting manual preprocessing efforts by 40%. • Built Power BI dashboards tracking feature drift, model health KPIs, and customer behavior clusters for strategic planning. • Participated in internal AI guild initiatives to pilot LLM-based document summarization using Hugging Face models and Azure Cognitive Services. • Deployed batch inference pipelines, serving daily scoring outputs to CRM and campaign teams.
Job description
• Conducted predictive modeling research on urban mobility datasets, developing a graph neural network (GNN) prototype for optimizing traffic flow predictions. • Processed 50GB+ GPS trajectory data using PySpark, resulting in a 35% reduction in training time compared to legacy pandas based approaches. • Published findings in an internal research report, highlighting the potential of temporal graph analytics for smart city initiatives. • Assisted faculty on curriculum enhancement, adding real-world MLOps content (MLflow, Airflow) into the university's ML engineering courses.
Job description
• Built and optimized ETL pipelines for marketing analytics datasets using AWS S3, Airflow, and PostgreSQL, handling daily ingestion of 5M+ records. • Designed and deployed Star and Snowflake schemas to improve analytical query speeds by 50%, enabling near real-time reporting. • Automated metadata tracking with Python scripts, improving audit readiness and data lineage visibility across systems. • Implemented SQL-based feature stores supporting churn prediction and fraud detection models, reducing feature engineering rework by 30%. • Collaborated with ML teams to ensure production data pipelines met model freshness SLAs.
Job description
• Built initial churn prediction model using logistic regression and random forests, increasing early warning system precision by 15% . • Conducted feature selection experiments using recursive feature elimination (RFE) to optimize model interpretability. • Delivered quarterly customer insights reports using Python visualizations, improving executive stakeholder engagement with data driven decisions. • Presented findings to marketing and sales leadership, influencing campaign re-targeting strategies for at-risk segments. • Drafted ML pipeline blueprints, laying groundwork for future predictive analytics roadmap.
Recent position
01/01/2025
-
05/02/2025
Skills
Unsupervised Learning
Transformers (Electrical)
MySQL
Git (Version Control System)
Azure Data Factory
Data Science
Automation
Tableau (Business Intelligence Software)
Scikit-Learn (Python Package)
Deep Learning
Jupyter
Machine Learning
MongoDB
Bash (Scripting Language)
Java (Programming Language)
Groundwork (Construction)
Logistic Regression
Customer Service
Leadership
FastAPI
Visualization
Customer Relationship Management
Pandas (Python Package)
Airflow
Power BI
Sales
Amazon Web Services
Complexity Reduction
Prototype (Manufacturing)
Customer Insights
Amazon S3
Research
Fraud Detection
Docker (Software)
Scale (Map)
Azure Databricks
Marketing Analytics
SQL (Programming Language)
Data Lineage
Xgboost
Marketing
Feature Selection
Analytics
Python (Programming Language)
Hugging Face Transformers
Seaborn
Matplotlib (Python Package)
Financial Services
Raw Data
VS Code
TensorFlow
Data Engineering
PostgreSQL
Feature Engineering
Traffic Flow
LightGBM
Metadata
PySpark
MLflow
Stakeholder Engagement
Predictive Modeling
Trajectory
Dilution Of Precision (GPS)
Data Pipelines
Databricks
Boosting
Electronic Design Automation (EDA) Software
Data Processing
Extract Transform Load (ETL)
Predictive Analytics
Your hiring pipeline, powered by AXIOM PRO.
Top candidates, pre-vetted — no hire, no charge
Talent Review Date: 07/15/2025
Recent position
Data Scientist | Product
Junior Data Scientist
02/01/2024 - 05/02/2025Job Description
• Perform end-to-end ML/AI modeling processes for data science projects to help improve marketing and campaign performance, including: • Understanding business objectives and translating them into data-driven solutions. • Accessing and extracting data from diverse and large-scale sources, such as sales, service records, client demographics, marketing campaigns, facilities, infrastructure, staffing, financials, and more. • Performing data cleaning, integration, and quality control to ensure data accuracy and usability. • Conducting exploratory data analysis (EDA) using summary statistics, aggregations, feature engineering, and random sampling techniques to find data insights and prepare data for modeling. • Building and developing ML/AI models tailored to the project goals. • Validating and selecting the optimal model by evaluating robustness and stability. This includes calculating key performance metrics such as accuracy, ROC, AUC, capture rate, lift, decile analysis, scoring, and overall population performance. • Providing actionable recommendations based on model insights to project managers and clients. • Documenting the full workflow and delivering clear, comprehensive reports. • Deploying models and creating implementation codes to support automation. • Projects in the past year: • Nissan EV re-purchase predictive model. • Brookdale senior living center monthly campaign predictive models (for assisted living, independent living, and memory care units). • KIA re-purchase recommendation model. • Hyundai multi-classifier re-purchase recommendation model. • KIA multi-label service recommendation model. • Brookdale senior living community forecast model. • KIA service feedback sentiment analysis, service theme clustering and voice of customer model. • Nissan open-retail re-purchase predictive model. • BMW Teleservice inactive user service predictive model.
Smarter hiring with AI
Your hiring pipeline, powered by AXIOM PRO .
Top candidates, pre-vetted — no hire, no charge
Talent Review Date: 07/15/2025
Video presentation
WORKPLACES
Job description
• Perform end-to-end ML/AI modeling processes for data science projects to help improve marketing and campaign performance, including: • Understanding business objectives and translating them into data-driven solutions. • Accessing and extracting data from diverse and large-scale sources, such as sales, service records, client demographics, marketing campaigns, facilities, infrastructure, staffing, financials, and more. • Performing data cleaning, integration, and quality control to ensure data accuracy and usability. • Conducting exploratory data analysis (EDA) using summary statistics, aggregations, feature engineering, and random sampling techniques to find data insights and prepare data for modeling. • Building and developing ML/AI models tailored to the project goals. • Validating and selecting the optimal model by evaluating robustness and stability. This includes calculating key performance metrics such as accuracy, ROC, AUC, capture rate, lift, decile analysis, scoring, and overall population performance. • Providing actionable recommendations based on model insights to project managers and clients. • Documenting the full workflow and delivering clear, comprehensive reports. • Deploying models and creating implementation codes to support automation. • Projects in the past year: • Nissan EV re-purchase predictive model. • Brookdale senior living center monthly campaign predictive models (for assisted living, independent living, and memory care units). • KIA re-purchase recommendation model. • Hyundai multi-classifier re-purchase recommendation model. • KIA multi-label service recommendation model. • Brookdale senior living community forecast model. • KIA service feedback sentiment analysis, service theme clustering and voice of customer model. • Nissan open-retail re-purchase predictive model. • BMW Teleservice inactive user service predictive model.
Job description
• Managing and developing data quality assurance for multiple projects and data systems, including educational entity, financial, student/staff demographic, and student performance data. E-Mail: xinliu.co@gmail.com Cell Phone: 720-695-8191 • Building and writing programming codes for application data elements and business rules. • Implementing common data standards to map from the raw data resources, ensuring compliance with regulatory requirements and data governance practices. • Creating and using standard macro programs in SAS to support data quality checks and analysis. • Conducting comprehensive data analysis, generating data tables, listings, and summary reports and responding to inquiries from internal stakeholders and external clients.
Job description
• Designing automotive accessory products using AutoCAD • Managing the associated manufacturing processes, monitoring product quality, and generating detailed performance and production reports.
Job description
• Conducting field, area, and basin studies, and managing geological data, including cleaning, verifying data sources, and reviewing datasets to ensure accuracy, consistency, and integrity. • Providing petrophysical log data management and technical support to team members, including editing and normalizing log data, working with tops and maps, calibrating core-to-log data and well test data, and validating and integrating fracture and production data. • Developing and maintaining data-driven quantitative petrophysical models and managing the resulting datasets to support integrated workflows across the team. • Preparing presentations and reports that offer recommendations for operational strategies and business decisions, with a focus on enhancing long-term production and reducing total costs.
Job description
• Providing academic and administrative committee services. • Delivering lectures, including Electronic Circuits, Linear System, Pattern Recognition (Data Mining). • Conducting research focused on data modeling and statistical analysis using C++, MATLAB, SAS.
Job description
• Leading research, managing data, coordinating laboratory operations and contributing to academic publishing. • Applying the model-based POD (Probability of Detection) techniques to improve the reliability of steam generator tube inspection.
Recent position
02/01/2024
-
05/02/2025
Skills
Jupyter
Time Series
Scikit-Learn (Python Package)
AutoCAD
Python (Programming Language)
Amazon Web Services
NumPy (Python Package)
Recurrent Neural Network (RNN)
Power BI
SQL (Programming Language)
Microsoft Excel
Pandas (Python Package)
Keras (Neural Network Library)
Deep Learning
Writing
Quality Control
MATLAB
Data Modeling
Senior Living
Sampling (Statistics)
Marketing
R (Programming Language)
SAS (Software)
Data Analysis
Customer Relationship Management
Quality Assurance
Sales
Coordinating
Operations
Management
Technical Support
Reliability
Editing
Electronic Circuits
Sentiment Analysis
Presentations
Governance
Business Objectives
Pattern Recognition
Data Science
Exploratory Data Analysis
Research
C (Programming Language)
Assisted Living
PyTorch (Machine Learning Library)
Long Short-Term Memory (LSTM)
Feature Engineering
Data Management
Microsoft Visual Studio
Matplotlib (Python Package)
Seaborn
TensorFlow
Jupyter Notebook
Postdoctoral Research
Manufacturing Processes
Good Manufacturing Practices
Raw Data
Test Data
Product Quality (QA/QC)
Data Quality
Probability
Regulatory Requirements
Electronic Design Automation (EDA) Software
Statistics
Statistical Analysis
Data Governance
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Gary Volochinsky
ITLC Manager | Medical Diagnostic Laboratories LLC
I am very pleased with the whole process and services Axiom has provided during our search for ITLC Support Specialist. Hiring Anzhelika was a very good choice, as she has been able to learn and follow MDL work flow and became a great asset to the ITLC team in a short period of time. I will definitely utilize your services for any future positions needs.
Sarah Landenwitsch
Vice President & Managing Member | STATKING Clinical Services
I appreciate everything you've done to help us so far. This process has been very easy. I have nothing but positive things to say about Vigen. He has been a great addition to our team. He’s reliable and enthusiastic when it comes to working on any project that I have given him. Vigen has also made suggestions that we will look to implement here as well. Overall, I am very pleased to have him on our team.
Charu Trikannad
Director of IT – Business Applications
I am happy to inform you that Nanda is excellent and is passionate about the work assigned to her. Communication, collaboration is perfect and excellent analytical skills. She understands relationships between entities and has drawn ER Diagrams. It’s a pleasure working with her. Hope it continues that way.
Angelique Munoz
IT Coordinator | Information Technology Department | Genesis Biotechnology Group
We are extremely satisfied with the team that you have provided to us! They are doing exceptionally well.
Jason West-McReynolds
Co-Founder | Fran Metrics
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Ecommerce and ERP Solutions Architect | Firecommerce
Axiom recruitment service provided the quality of candidate I needed for a personal assistant. The cultural fit is perfect as much as the skills and experience required for the job. I appreciate the dedication and speed with which they delivered this job!
Alex Greenberg
Managing Partner | Vivat, Inc.
Exceptional Recruiting Firm – Highly Recommended! We urgently needed to find qualified resources for a strategic initiative. Axiom Pro quickly became an invaluable partner in our quest to find top-tier talent for our company. Their highly personable, professional, and responsive team has shown us their dedication to understanding our hiring needs. They took the time to thoroughly vet candidates, ensuring we only met with the best fit for our organization. Thanks to Axiom Pro, we discovered fantastic people who seamlessly blended into our group and made a powerful impact. Axiom Pro's unique approach to the recruitment process, which combines personalized techniques with GenAI capabilities, truly sets them apart from other firms, making them an exclusive choice for top-tier talent. If you're looking for a dedicated, creative, reliable, and trustworthy recruiting firm that delivers quality candidates and exceptional service, I can't recommend Axiom Pro highly enough!
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Chief Information Officer | IT Strategy & Digital Transformation | Business-Aligned Technology Leader at Genesis Global Group.
We have been working with Axiom Pro for over 8 years, leveraging their expertise to augment our in-house IT team. This partnership has been instrumental in enabling us to bring new products and services to market faster, while maintaining exceptional quality. Axiom Pro has played a key role in our success by helping us create a highly effective hybrid model, providing access to top-tier IT talent including Business Analysts, Developers, Architects, QA specialists, and Release Managers. As a multi-vertical company, we manage and support a diverse portfolio of applications across different industries. In just the last year, with Axiom Pro’s support, we successfully developed and deployed a custom AI application—further accelerating innovation and expanding our capabilities. Axiom Pro has consistently demonstrated the ability to assist in most areas of our operations, providing reliable, skilled, and scalable resources when we need them most. Our long-term collaboration with Axiom Pro has been extremely productive, and we are very satisfied with the outcomes. They are more than just a vendor—they are a trusted partner in our growth and innovation.
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